Along with development of multimedia technology, demand on high-definition image is gradually increased. Image quality is greatly related to the amount of noises generated during an image capturing process, a signal conversion process and a transmission process. In order to effectively remove the noises to improve the image quality, researches on noise elimination in the image processing domain draws more and more attention. A reason for the formation of the noise is, for example, variation of ambient light source which results in generation of random noise on an image capturing unit, noises generated by the circuit itself, or noises generated during an image processing process (for example, white balance, image interpolation). Therefore, images captured in the night generally have strong noises.
In filtering processing, a filter is generally used to adjust pixel values of an image, so as to eliminate the noise. However, if the pixel values are excessively adjusted to eliminate the noise, image details are also weakened to cause unclarity of the image. Therefore, it is required to reach a balance between clarity of image details and noise elimination.
In the current image noise reducing technique, a weight value of a filter can be dynamically adjusted to implement image filtering processing to achieve a good noise reducing effect, though it has problems of high operation complexity and requiring an additional reference image to cause memory consumption, etc. which results in a fact that the noise reducing techniques are not easy to be integrated to a video encoder or a digital signal processor.